Therapeutic targeting of white adipose tissue metabolic dysfunction in obesity: mechanisms and opportunities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
White adipose tissue is not only a highly heterogeneous organ containing various cells, such as adipocytes, adipose stem and progenitor cells, and immune cells, but also an endocrine organ that is highly important for regulating metabolic and immune homeostasis. In individuals with obesity, dynamic cellular changes in adipose tissue result in phenotypic switching and adipose tissue dysfunction, including pathological expansion, WAT fibrosis, immune cell infiltration, endoplasmic reticulum stress, and ectopic lipid accumulation, ultimately leading to chronic low-grade inflammation and insulin resistance. Recently, many distinct subpopulations of adipose tissue have been identified, providing new insights into the potential mechanisms of adipose dysfunction in individuals with obesity. Therefore, targeting white adipose tissue as a therapeutic agent for treating obesity and obesity-related metabolic diseases is of great scientific interest. Here, we provide an overview of white adipose tissue remodeling in individuals with obesity including cellular changes and discuss the underlying regulatory mechanisms of white adipose tissue metabolic dysfunction. Currently, various studies have uncovered promising targets and strategies for obesity treatment. We also outline the potential therapeutic signaling pathways of targeting adipose tissue and summarize existing therapeutic strategies for antiobesity treatment including pharmacological approaches, lifestyle interventions, and novel therapies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it